Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,84 @@
+---
+license: mit
+language:
+- en
+metrics:
+- accuracy
+pipeline_tag: text-generation
+widget:
+- text: <schema>CREATE TABLE radio(age VARCHAR, radio_id VARCHAR,  frequency VARCHAR,
+    wavelength VARCHAR); CREATE TABLE  radio_faults(radio_id VARCHAR, fault_description
+    VARCHAR)</schema><question>Get the radio id and defect descriptions of radios
+    that have wavelength greater than 30 ?</question><sql>
+  example_title: example1
+- text: '<schema>CREATE TABLE system(JobID: String,GID: String, UID: String, Start:Time(yyyy/mm/dd),
+    End: Time,ElapsedRaw: Time, CPUTimeRAW: Time,NCPUS: Number,NNodes: Number, NodeList:
+    List,  State:String, Timelimit: Time);</schema><question>Get UID and job id for
+    Jobs that started on Jan 20 , 2023</question><sql>'
+  example_title: example2
+- text: <schema>CREATE TABLE department (Department_ID number, Name text, Creation
+    text, Ranking number, Budget_in_Billions number, Num_Employees number) which has
+    Department_ID as primary key abd CREATE TABLE head (head_ID number, name text,
+    born_state text, age number) which has head_ID as primary key and CREATE TABLE
+    management (department_ID number, head_ID number, temporary_acting text) which
+    has department_ID as primary key</schema><question>
+  example_title: example3
+tags:
+- code
+- sql
+- text2sql
+- instruction_tuned
+- jax
+- pytorch
+- 1b
+- expert
+- llama-cpp
+- gguf-my-repo
+datasets:
+- PipableAI/spider-bird
+base_model: PipableAI/pip-SQL-1B
+---
+
+# marroyo777/pip-SQL-1B-Q4_K_M-GGUF
+This model was converted to GGUF format from [`PipableAI/pip-SQL-1B`](https://huggingface.co/PipableAI/pip-SQL-1B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/PipableAI/pip-SQL-1B) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo marroyo777/pip-SQL-1B-Q4_K_M-GGUF --hf-file pip-sql-1b-q4_k_m-imat.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo marroyo777/pip-SQL-1B-Q4_K_M-GGUF --hf-file pip-sql-1b-q4_k_m-imat.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo marroyo777/pip-SQL-1B-Q4_K_M-GGUF --hf-file pip-sql-1b-q4_k_m-imat.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo marroyo777/pip-SQL-1B-Q4_K_M-GGUF --hf-file pip-sql-1b-q4_k_m-imat.gguf -c 2048
+```